Dynamic inclusion thresholds for social network conversations

ABSTRACT

A social network conversation dynamic inclusion threshold causes a first subset of social network group members of a social network group to be included in a social network conversation earlier than at least one other social network group member. In accordance with the social network conversation dynamic inclusion threshold, social network posts of the social network conversation are distributed to the first subset of social network group members while delaying distribution of the social network posts of the social network conversation to the at least one other social network group member. Upon satisfaction of the social network conversation dynamic inclusion threshold, the social network posts of the social network conversation are distributed to the at least one other social network group member.

BACKGROUND

The present invention relates to social network communications. Moreparticularly, the present invention relates to dynamic inclusionthresholds for social network conversations.

Social networks provide social network users with a way to communicatewith one another in an online environment. The social network users mayshare photographs and stories, and may communicate with each otherwithin the social network environment.

SUMMARY

A computer-implemented method includes: distributing, in accordance witha social network conversation dynamic inclusion threshold that causes afirst subset of social network group members of a social network groupto be included in a social network conversation earlier than at leastone other social network group member, social network posts of thesocial network conversation to the first subset of social network groupmembers while delaying distribution of the social network posts of thesocial network conversation to the at least one other social networkgroup member; and distributing, in response to satisfaction of thesocial network conversation dynamic inclusion threshold, the socialnetwork posts of the social network conversation to the at least oneother social network group member.

A system that performs the method and a computer program product thatcauses a computer to perform the method are also described.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example of an implementation of a systemfor dynamic inclusion thresholds for social network conversationsaccording to an embodiment of the present subject matter;

FIG. 2 is a block diagram of an example of an implementation of a coreprocessing module capable of performing dynamic inclusion thresholds forsocial network conversations according to an embodiment of the presentsubject matter;

FIG. 3 is a flow chart of an example of an implementation of a processfor dynamic inclusion thresholds for social network conversationsaccording to an embodiment of the present subject matter;

FIG. 4 is a flow chart of an example of an implementation of a processfor configuration of dynamic inclusion thresholds for social networkconversations according to an embodiment of the present subject matter;and

FIG. 5 is a flow chart of an example of an implementation of a processfor performing and dynamically adjusting dynamic inclusion thresholdsfor social network conversations according to an embodiment of thepresent subject matter.

DETAILED DESCRIPTION

The examples set forth below represent the necessary information toenable those skilled in the art to practice the invention and illustratethe best mode of practicing the invention. Upon reading the followingdescription in light of the accompanying drawing figures, those skilledin the art will understand the concepts of the invention and willrecognize applications of these concepts not particularly addressedherein. It should be understood that these concepts and applicationsfall within the scope of the disclosure and the accompanying claims.

The subject matter described herein provides dynamic inclusionthresholds for social network conversations. The technology describedherein solves a recognized social network conversation problem byproviding a new form of computing technology that dynamically includessocial network users within social network conversations over time inaccordance with social network conversation dynamic inclusionthresholds. The social network conversation problem was recognized asresulting from online communications lacking face-to-face feedback ofhow commentary is perceived by other group members. As a consequencecertain social network group members may not post their contributions tosocial network conversations to avoid perceived contradiction of othermembers. This social network conversation problem was recognized to becompounded in circumstances where certain styles of commentary (e.g., astrong positive or negative opinion) are expressed by the other membersearly in an online conversation. This dynamic of social networkconversations was determined to cause conversations to terminate earlierthan they otherwise would terminate, with a coincident lack ofsufficient diversity and objectivity of perspective to provide objectivevalue to social network groups as a whole.

To solve this recognized problem, and to enhance diversity andobjectivity of perspective in social network conversations, the presenttechnology provides social network conversation dynamic inclusionthresholds (hereinafter “dynamic inclusion thresholds” for ease ofreference). The dynamic inclusion thresholds may be configured toprogrammatically provide certain identified social network group membersthat otherwise may not contribute to social network conversations withan opportunity to contribute and be included in online conversations bydelaying delivery of social network posts to social network groupmembers that historically post commentary that may lack objectivecontribution/assistance to other members of the social network group. Assuch, the dynamic inclusion thresholds perform a dual role of operatingto dynamically “include” members of social network groups that otherwisemay not contribute to social network conversations, and by alsocontemporaneously operating to dynamically “include” members withparticular styles of historical communication patterns to conversationsover time. Both forms of inclusion may be dynamically adjusted in realtime as social network conversations unfold within a social network.Accordingly, the present technology may facilitate more balanced,objective, and comprehensive social network conversations with anincreased diversity of participants, commentary, and perspective.

In operation, a social network conversation dynamic inclusion thresholdis obtained that causes a first subset of social network group membersto be included in a social network conversation earlier than at leastone other social network group member and that further causes the atleast one other social network group member to be included in the socialnetwork conversation responsive to satisfaction of the configured socialnetwork dynamic inclusion threshold. In accordance with the configuredsocial network conversation dynamic inclusion threshold, social networkposts of the social network conversation are contemporaneously deliveredto the first subset of social network group members while delivery isdelayed to the at least one other social network group member. Inresponse to satisfaction of the social network conversation dynamicinclusion threshold, the social network posts of the social networkconversation are distributed to the at least one other social networkgroup member.

The social network group members for which delivery of posts is delayedmay be determined, for example by text analysis of social networkconversations over time, to express a particular style of commentary(e.g., a strong opinion, un-objective commentary, etc.) that is alsodetermined over time, again such as by text analysis of social networkconversations, to deter commentary and contribution from other groupmembers. The dynamic inclusion thresholds allow these other socialnetwork group members that first receive the social network posts tocontribute to social network conversations without feeling like theconversation is already concluded and without feeling that commentarymay be perceived as contradicting strong opinions of others expressedearlier in the online conversation. The social network group member withthe particular style of commentary may be included in social networkconversations after the configured dynamic inclusion threshold issatisfied or expired to ensure that all social network group membershave an opportunity to contribute to the online conversation.

As described above and in more detail below, social networkconversations of a social network group may be analyzed over time torecognize patterns of both communication and non-communicationresponsive to commentary by other group members. Trends of responserates may also be analyzed, such as response rates of social networkusers relative to one another. For example, the present technology maydetermine by analysis of social network conversations that certainsocial network group members contribute to conversations when providedwith a reasonable opportunity (e.g., time period or other criteria) tocontribute, but that these same social network group members do notcontribute if a particular style of perspective has already beenexpressed/communicated. In such a circumstance, the present technologymay infer that these social network group members interpret theconversation to be concluded or that commentary may be perceived ascontradicting opinions of other, and may further infer that the groupmember with the particular style of perspective may feel a need toreiterate their perspective if any other commentary is added to theconversation. While this is a delicate situation among social networkgroup members, the present technology operates programmatically tomitigate these types of potentially unintentional interactions that maybe perceived to actually inhibit open communication and participationwithin social network groups over time. As such, the present technologyimplements the dynamic inclusion thresholds to attempt to foster andbuild coherence and to strengthen social network groups over time byensuring that all group members have a chance to express their opinionsand comment on issues that are relevant to the particular social networkgroup.

As introduced above, a particular social network group member that, forexample, dominates social network conversations may beinferred/determined by analytical recognition that other social networkgroup members contribute to the social network conversations less oftenwhen the particular social network group member contributes with aparticular style of commentary (e.g., such as by contributing early inthe conversation with a positive or negative strong opinion). Thistendency to express strong opinions earlier in conversations may beexacerbated where the dominant social network group member is onlinemore often than other group members.

A social network conversation dynamic inclusion threshold may beconfigured that causes certain social network group members to beincluded earlier in future online conversations and that causes othersocial network group members to be included later in conversations(e.g., particular members may be deferred from initial inclusion in afuture online conversation). As such, the present technology allowsother social network group members to have an opportunity to contributeto the conversation before the conversation appears objectively to havebeen concluded without the added value of their contribution(s).Distribution of social network posts associated with the social networkconversation may be deferred from delivery to the particular socialnetwork group member with stronger opinions in accordance with aconfigured social network conversation dynamic inclusion threshold,while the social network posts are delivered to other social networkgroup members to provide them with an opportunity to contribute wherethey may not otherwise contribute if a strong opinion had been expressedearly in the online conversation.

The social network posts associated with the social network conversationmay be delivered to the particular social network group member inresponse to satisfaction or expiration of the social networkconversation dynamic inclusion threshold, at which time the particularsocial network group member may contribute that user's particular styleof commentary without squelching the conversation among the group. Thisform of dynamic inclusion of the particular social network group memberfurther fosters a recognition among the social network group that theopinions and commentary of that particular social network group memberare valued among the group, with the recognition that group members ofstronger opinion should still embrace the opportunity to communicatewith the group, whether earlier or later in a particular conversation.

An ordering of distribution of social network posts may be controlledwithin a social network to ensure that a balanced set of responses areavailable to users that post inquiries or comments within a socialnetwork. The present technology evaluates members of an online socialnetwork, and response histories of the respective members. Responsive todetection of a new post, the post is intercepted and a distribution listis created for the post in accordance with the members of the socialnetwork group. A first intended candidate subset of members of the groupon the distribution list is selected in accordance with a configureddynamic inclusion threshold, and the post may be initially distributedto the selected subset of members of the group. The selected subset maybe derived based upon members from which historical responses aredetermined to be lacking due potentially to dominant responses fromother members of the group, based upon users being involved primarilywith different aspects of a subject matter area within the group, orbased upon other criteria as appropriate for a given implementation. Theconversation (e.g., set of responses) may be monitored and compared to adynamic inclusion threshold. When the conversation reaches a targetpoint of diversity of opinion, time, or other factors that areconfigured for the dynamic inclusion threshold, such as responsesappearing from the initial subset of members, the visibility of thepost/conversation may be expanded to include more members of the socialnetwork group. Over time, other members of the group may be added fromthe distribution list and the post may be distributed to the addedmembers for comment and/or response until all members have had a chanceto view the post and comment and/or respond. As such, the dynamicinclusion thresholds may be altered over time, which allow other peopleto also be included in the conversation. By time shifting the potentialfor inclusion of stronger opinions to later in social networkconversations, the present technology may provide more incentive togroup members that are online less often to contribute to social networkconversations.

The mixture of social network group members included in a social networkconversation may include members with both positive and negativeopinions, different interests, and other diversity of expressions, thatare incorporated into the responses in a dynamic and systematic mannerover time. The present technology may perform real-time monitoring andtext analysis of social network conversations to determine whetherdiffering opinions have been sufficiently expressed by a subset ofmembers to reasonably diversify the particular conversation. The dynamicinclusion thresholds may be adjusted in real time in response to textanalytics of the social network conversations. As such, where aparticular user has been deferred from initial inclusion in aconversation, that particular user may be added to the conversation inresponse to analysis of the content of the conversation and thediversity of commentary that has already occurred in the conversation.

This commentary mixture over time allows more passive or neutralparticipants that may otherwise not participate at all in conversationsto observe diversity of opinion (rather than one-sided commentary) thatmay attract commentary from those participants, and that may furtherallow those participants to contribute earlier in conversations, whilestill including participants with stronger opinions (positive ornegative, and that would likely participate regardless of timing) toparticipate later in a conversation. Further, the timing of inclusion ofgroup members may be dynamically adjusted as conversations unfold in asocial network environment.

The present technology may leverage streamed post distributiontechniques or hide date/time stamps to mask the inclusion thresholds sothat all users appear to have a balanced opportunity to present theircommentary. As such, the present technology allows social networkconversations to be developed with a balanced set of opinions beingexpressed for consideration by the person that initiated the post,rather than just receiving one-sided responses (again either positive ornegative).

The dynamic inclusion thresholds may be based upon a variety ofdifferent dynamic inclusion criteria. For example, the dynamic inclusioncriteria may include an elapsed amount of time (e.g., a timeout, such asone minute, one hour, one day, etc.). Additional and/or alternativedynamic inclusion criteria may include quality and diversity of opinionsexpressed within responses, sentiment of responses, attainment of ameta-threshold (e.g., quantity of responses, such as that there havebeen ten new posts, specific social network group members have joinedthe conversation, etc.), a number of responses or rate of responsesincreasing or decreasing (e.g., a detected positive or negative changein a rate of responses), a sentiment threshold (more positive responsesthan negative responses, etc.), subject matter drift, negativitytolerance criteria, age of posts, thread size, or other threshold, asappropriate for a given implementation. The dynamic inclusion thresholdsmay be implemented as a combination of the various dynamic inclusioncriteria. Further, many different forms of dynamic inclusion criteriaare possible and all such possibilities are considered within the scopeof the present technology.

The dynamic inclusion thresholds may be configured as dynamic inclusionrules that are evaluated in response to each post or each set of poststo a particular online conversation. The dynamic inclusion rules may beformed based upon, for example, the following criteria: “Include peoplewith interest profiles that match subject X initially, and after 2 hoursalso include people with interest profiles that match subject Y.”Alternatively, the dynamic inclusion rules may be formed based upon, forexample, the following criteria: “Include people that contribute lessoften initially, and after ten posts have been generated include othergroup members.” Many other variations of dynamic inclusion rules arepossible, and all such variations are considered to be within the scopeof the present technology.

The present technology may also apply to any electronic mail client. Assuch, electronic mail messages may also be processed as otherwisedescribed herein with respect to social network posts.

Several additional aspects of the present technology relating to theinclusion or exclusion thresholds are described below, and each may beimplemented as appropriate for a given implementation. For example, arequest to repost or share the contents of a post may be detected, andbecause a reposting or sharing of the content may make the full postavailable for all to see without use of the technology described herein,the same access rules as utilized during the initial postings may beapplied to the new post. The present technology may be activated only onpeer review around social/collaborative artifacts. Further, a votingsystem may be implemented that allows participants to vote on whether tomake the post visible to a wider audience, thus by majority (or otherthreshold vote) those who were previously excluded from the discussionthread may be included by consensus.

The technology described herein may be applied to sets of social networkgroup members by combining multiple users' social network responsesand/or commentaries. A system may be implemented to include sentimentmetrics between pairs of users in the social network.

It should be noted that additional members may be added from the socialnetwork into a conversation randomly. Additionally, a user interfaceselection may be provided to allow marking of a conversation as completeor ready for full distribution.

A negative or positive perception within subsets of responses may alsobe identified and displayed. For example, if a social network user isinterested in providing a comment on a hotel, the user may selectivelysee what other reviews have been posted with a similar sentiment of thepost the user is interested in providing, which may assist with furtherenhancing diversity of commentary by allowing the user to augment,rather than repeat, the other postings of similar sentiment.

Further regarding response histories of the respective members, usersmay be added initially to the distribution list from a top percentagelevel (e.g., top quartile or other histogram) based upon theirhistorical responses. Users may be added to the distribution of aresponse over time by adjusting the percentage level of users to beincluded in the distribution.

Users may additionally be added for distribution over time (e.g.,initial distribution versus additional recipients) by use of astatistical confidence level in an expected form of response to aparticular initial post. Use of a statistical confidence level mayprovide progressive access to additional participants over time.

Additionally, a temporary circle, distribution list, or group may becreated and used for both initial and subsequent additions to thedistribution of a post in a social network conversation. New socialnetwork groups may also be created to further distribute posts to othersocial network members (e.g., other than the core social network group)to elicit more commentary from other social network users or from othersocial networks. These calculated groups may be stored for reuse.Clustering or grouping of individuals may be achieved by any of thefollowing methods: frequency of communication and “inner circle”sentiment of a prior communication, expertise related to the post,groupings of individual members of the group, personal sentiment relatedto the topic (e.g., really like or dislike the topic), predictability inresponse (e.g., predictability of either a positive or negativesentiment in the absence of expertise), prior combinations of responses,clusters of prior responses, likelihood of response, trust metrics,temporal aspects, and features of the message. It should be understoodthat the subject matter described herein is not limited to the listingabove and that other approaches to clustering or grouping are possibleand may be utilized as appropriate for the respective implementation.

It should be noted that conception of the present subject matterresulted from recognition of certain limitations associated with socialnetwork conversations. For example, it was observed that because socialnetworks allow users to comment essentially at will during all hours ofdays and nights, social network users often engage in conversations thatevolve by a first user that sees a post often being the first user torespond. This tendency was observed to result in a form of “first in,first out” (FIFO) messaging within a social network that, whilepotentially efficient for messaging mechanics, may lead todissatisfaction among social network users if certain users are moreactive and thereby are able more often to comment first. It was observedthat because of the social nature of social networks (e.g., a lack offace-to-face feedback of how commentary is actually perceived by othergroup members), certain social network users may not recognize how theircommentary is perceived by other users, and as a result many other usersmay not express their opinions if more active users are perceived tohave squelched a conversation. It was determined that this dynamicnature of social network communications may lead to a lack ofparticipation among certain social network users that also have valuableknowledge or objective and insightful contributions but that hesitate tocontribute once strong responses have been entered/posted. It wasdetermined that new technology that addresses this problem may implementa dynamic threshold for inclusion of social network users in socialnetwork conversations, by which inclusion of social network users insocial network conversations may be dynamically adjusted over time, toallow less active social network users to participate earlier in socialnetwork conversations to enhance idea sharing and to avoid one-sidedconversations. The present subject matter improves social networkconversations and information sharing within social networks byproviding for improved social network conversation focus by dynamicalteration of a threshold of inclusion of group members into the socialnetwork conversations, as described above and in more detail below. Assuch, improved social network conversations may be obtained through useof the present technology.

The dynamic inclusion thresholds for social network conversationsdescribed herein may be performed in real time to allow promptthreshold-based inclusion of participants to social networkconversations. For purposes of the present description, real time shallinclude any time frame of sufficiently short duration as to providereasonable response time for information processing acceptable to a userof the subject matter described. Additionally, the term “real time”shall include what is commonly termed “near real time”-generally meaningany time frame of sufficiently short duration as to provide reasonableresponse time for on-demand information processing acceptable to a userof the subject matter described (e.g., within a portion of a second orwithin a few seconds). These terms, while difficult to precisely defineare well understood by those skilled in the art.

FIG. 1 is a block diagram of an example of an implementation of a system100 for dynamic inclusion thresholds for social network conversations. Acomputing device_1 102 through a computing device_N 104 communicate viaa network 106 with several other devices. The other devices include aserver_1 108 through a server_M 110, and a database 112.

As will be described in more detail below in association with FIG. 2through FIG. 5, the computing device_1 102 through the computingdevice_N 104 and/or the server_1 108 through the server_M 110 may eachprovide automated dynamic inclusion thresholds for social networkconversations. The automated dynamic inclusion thresholds for socialnetwork conversations is based upon historical and real-time analysis ofsocial network conversations to determine patterns of non-communicationby certain group members and to increase diversity of social networkconversations based upon this analysis by inclusion of group membersthat may otherwise not contribute to conversations under certain typesof situations. The automated dynamic inclusion thresholds for socialnetwork conversations also operates to dynamically include differentsocial network members with different or stronger opinions over time toavoid leaving those social network group members out of conversations.The present technology may be implemented at a user computing device orserver device level, or by a combination of such devices as appropriatefor a given implementation. A variety of possibilities exist forimplementation of the present subject matter, and all such possibilitiesare considered within the scope of the present subject matter.

The network 106 may include any form of interconnection suitable for theintended purpose, including a private or public network such as anintranet or the Internet, respectively, direct inter-moduleinterconnection, dial-up, wireless, or any other interconnectionmechanism capable of interconnecting the respective devices.

The server_1 108 through the server_M 110 may include any device capableof providing data for consumption by a device, such as the computingdevice_1 102 through the computing device_N 104, via a network, such asthe network 106. As such, the server_1 108 through the server_M 110 mayeach include a social network server, web server, application server, orother data server device.

The database 112 may include multiple different databases and may storesocial network conversation content for use by one or more socialnetworks implemented by the server_1 108 through the server_M 110. Thedatabase 112 may include a relational database, an object database, orany other storage type of device. As such, the database 112 may beimplemented as appropriate for a given implementation.

FIG. 2 is a block diagram of an example of an implementation of a coreprocessing module 200 capable of performing dynamic inclusion thresholdsfor social network conversations. The core processing module 200 may beassociated with either the computing device_1 102 through the computingdevice_N 104 or with the server_1 108 through the server_M 110, asappropriate for a given implementation. As such, the core processingmodule 200 is described generally herein, though it is understood thatmany variations on implementation of the components within the coreprocessing module 200 are possible and all such variations are withinthe scope of the present subject matter.

Further, the core processing module 200 may provide different andcomplementary processing of dynamic inclusion thresholds in associationwith each implementation. As such, for any of the examples below, it isunderstood that any aspect of functionality described with respect toany one device that is described in conjunction with another device(e.g., sends/sending, etc.) is to be understood to concurrently describethe functionality of the other respective device (e.g.,receives/receiving, etc.).

A central processing unit (CPU) 202 (“processor”) provides hardware thatperforms computer instruction execution, computation, and othercapabilities within the core processing module 200. A display 204provides visual information to a user of the core processing module 200and an input device 206 provides input capabilities for the user.

The display 204 may include any display device, such as a cathode raytube (CRT), liquid crystal display (LCD), light emitting diode (LED),electronic ink displays, projection, touchscreen, or other displayelement or panel. The input device 206 may include a computer keyboard,a keypad, a mouse, a pen, a joystick, touchscreen, voice commandprocessing unit, or any other type of input device by which the user mayinteract with and respond to information on the display 204.

It should be noted that the display 204 and the input device 206 may beoptional components for the core processing module 200 for certainimplementations/devices, or may be located remotely from the respectivedevices and hosted by another computing device that is in communicationwith the respective devices. Accordingly, the core processing module 200may operate as a completely automated embedded device without directuser configurability or feedback. However, the core processing module200 may also provide user feedback and configurability via the display204 and the input device 206, respectively, as appropriate for a givenimplementation.

A communication module 208 provides hardware, protocol stack processing,and interconnection capabilities that allow the core processing module200 to communicate with other modules within the system 100. Thecommunication module 208 may include any electrical, protocol, andprotocol conversion capabilities useable to provide interconnectioncapabilities, as appropriate for a given implementation. As such, thecommunication module 208 represents a communication device capable ofcarrying out communications with other devices.

A memory 210 includes a historical social network conversation patternsstorage area 212 that stores within the core processing module 200analytical information and metrics regarding social network conversationdynamics derived over time by analysis of social network conversations.The analytical information and metrics regarding social networkconversation dynamics may include response rates (or non-response rates)and other information associated with social network group members underdiffering conversation circumstances and/or in response to commentary bydifferent members of social network groups. As will be described in moredetail below, the analytical information and metrics regarding socialnetwork conversation dynamics stored within the historical socialnetwork conversation patterns storage area 212 is used to configuresocial network conversation dynamic inclusion thresholds to both includemore participants in social network conversations and to includeparticipants over time to diversify the content expressed within socialnetwork conversations.

The memory 210 also includes a dynamic inclusion threshold configurationstorage area 214 that stores configured and dynamically updated socialnetwork conversation dynamic inclusion thresholds for particular socialnetwork groups, conversations, or other granularities as appropriate fora given implementation. As described above and in more detail below, theconfigured and dynamically updated social network conversation dynamicinclusion thresholds operate to include both persons that may otherwisenot contribute to social network conversations and to include otherpersons that are determined to be highly likely to contribute withstronger commentary over time. As described above, the configured anddynamically updated social network conversation dynamic inclusionthresholds perform a dual role of operating to “include” members ofsocial network groups that may otherwise not contribute to socialnetwork conversations, and by also contemporaneously operating to“include” members with particular styles of historical communicationpatterns to conversations over time. Both forms of inclusion may bedynamically adjusted in real time as social network conversations unfoldwithin a social network. Accordingly, the present technology mayfacilitate more balanced social network conversations with an increaseddiversity of participants, commentary, and perspective.

It is understood that the memory 210 may include any combination ofvolatile and non-volatile memory suitable for the intended purpose,distributed or localized as appropriate, and may include other memorysegments not illustrated within the present example for ease ofillustration purposes. For example, the memory 210 may include a codestorage area, an operating system storage area, a code execution area,and a data area without departure from the scope of the present subjectmatter.

A social network conversation dynamic inclusion threshold module 216 isalso illustrated. The social network conversation dynamic inclusionthreshold module 216 provides historical and real-time social networkconversation analysis for the core processing module 200, as describedabove and in more detail below. The social network conversation dynamicinclusion threshold module 216 implements the automated dynamicinclusion thresholds for social network conversations of the coreprocessing module 200.

It should also be noted that the social network conversation dynamicinclusion threshold module 216 may form a portion of other circuitrydescribed without departure from the scope of the present subjectmatter. Further, the social network conversation dynamic inclusionthreshold module 216 may alternatively be implemented as an applicationstored within the memory 210. In such an implementation, the socialnetwork conversation dynamic inclusion threshold module 216 may includeinstructions executed by the CPU 202 for performing the functionalitydescribed herein. The CPU 202 may execute these instructions to providethe processing capabilities described above and in more detail below forthe core processing module 200. The social network conversation dynamicinclusion threshold module 216 may form a portion of an interruptservice routine (ISR), a portion of an operating system, a portion of abrowser application, or a portion of a separate application withoutdeparture from the scope of the present subject matter.

A timer/clock module 218 is illustrated and used to determine timing anddate information, such as monitoring response timing of posts of socialnetwork conversations and satisfaction of time-based dynamic inclusionthresholds, as described above and in more detail below. As such, thesocial network conversation dynamic inclusion threshold module 216 mayutilize information derived from the timer/clock module 218 forinformation processing activities, such as the dynamic inclusionthresholds for social network conversations.

The database 112 is again shown within FIG. 2 associated with the coreprocessing module 200. As such, the database 112 may be operativelycoupled to the core processing module 200 without use of networkconnectivity, as appropriate for a given implementation.

The CPU 202, the display 204, the input device 206, the communicationmodule 208, the memory 210, the social network conversation dynamicinclusion threshold module 216, the timer/clock module 218, and thedatabase 112 are interconnected via an interconnection 220. Theinterconnection 220 may include a system bus, a network, or any otherinterconnection capable of providing the respective components withsuitable interconnection for the respective purpose.

Though the different modules illustrated within FIG. 2 are illustratedas component-level modules for ease of illustration and descriptionpurposes, it should be noted that these modules may include anyhardware, programmed processor(s), and memory used to carry out thefunctions of the respective modules as described above and in moredetail below. For example, the modules may include additional controllercircuitry in the form of application specific integrated circuits(ASICs), processors, antennas, and/or discrete integrated circuits andcomponents for performing communication and electrical controlactivities associated with the respective modules. Additionally, themodules may include interrupt-level, stack-level, and application-levelmodules as appropriate. Furthermore, the modules may include any memorycomponents used for storage, execution, and data processing forperforming processing activities associated with the respective modules.The modules may also form a portion of other circuitry described or maybe combined without departure from the scope of the present subjectmatter.

Additionally, while the core processing module 200 is illustrated withand has certain components described, other modules and components maybe associated with the core processing module 200 without departure fromthe scope of the present subject matter. Additionally, it should benoted that, while the core processing module 200 is described as asingle device for ease of illustration purposes, the components withinthe core processing module 200 may be co-located or distributed andinterconnected via a network without departure from the scope of thepresent subject matter. For a distributed arrangement, the display 204and the input device 206 may be located at a point of sale device,kiosk, or other location, while the CPU 202 and memory 210 may belocated at a local or remote server. Many other possible arrangementsfor components of the core processing module 200 are possible and allare considered within the scope of the present subject matter. It shouldalso be understood that, though the database 112 is illustrated as aseparate component for purposes of example, the information storedwithin the database 112 may also/alternatively be stored within thememory 210 without departure from the scope of the present subjectmatter. Accordingly, the core processing module 200 may take many formsand may be associated with many platforms.

FIG. 3 through FIG. 5 described below represent example processes thatmay be executed by devices, such as the core processing module 200, toperform the automated dynamic inclusion thresholds for social networkconversations associated with the present subject matter. Many othervariations on the example processes are possible and all are consideredwithin the scope of the present subject matter. The example processesmay be performed by modules, such as the social network conversationdynamic inclusion threshold module 216 and/or executed by the CPU 202,associated with such devices. It should be noted that time outprocedures and other error control procedures are not illustrated withinthe example processes described below for ease of illustration purposes.However, it is understood that all such procedures are considered to bewithin the scope of the present subject matter. Further, the describedprocesses may be combined, sequences of the processing described may bechanged, and additional processing may be added or removed withoutdeparture from the scope of the present subject matter.

FIG. 3 is a flow chart of an example of an implementation of a process300 for dynamic inclusion thresholds for social network conversations.The process 300 represents a computer-implemented method of performingthe dynamic inclusion thresholds for social network conversationsdescribed herein. At block 302, the process 300 obtains a social networkconversation dynamic inclusion threshold that causes a first subset ofsocial network group members of a social network group to be included ina social network conversation earlier than at least one other socialnetwork group member and that further causes the at least one othersocial network group member to be included in the social networkconversation responsive to satisfaction of the obtained social networkconversation dynamic inclusion threshold. At block 304, the process 300contemporaneously, in accordance with the obtained social networkconversation dynamic inclusion threshold, each of distributes socialnetwork posts of the social network conversation to the first subset ofsocial network group members and delays distribution of the socialnetwork posts of the social network conversation to the at least oneother social network group member. At block 306, the process 300distributes, in response to satisfaction of the social networkconversation dynamic inclusion threshold, the social network posts ofthe social network conversation to the at least one other social networkgroup member.

FIG. 4 is a flow chart of an example of an implementation of a process400 for configuration of dynamic inclusion thresholds for social networkconversations. The process 400 represents a computer-implemented methodof configuring the dynamic threshold-based inclusion for social networkconversations described herein. At decision point 402, the process 400makes a determination as to whether a request to configure a socialnetwork conversation dynamic inclusion threshold has been detected. Arequest to configure a social network conversation dynamic inclusionthreshold may be detected, for example, in response to a user request orotherwise as appropriate for a given implementation and may identify oneor more social network groups for which to configure a social networkconversation dynamic inclusion threshold. For purposes of thedescription below, it is presumed that one social network group has beenidentified for configuration of a social network conversation dynamicinclusion threshold, though additional processing to configure socialnetwork conversation dynamic inclusion thresholds for multiple socialnetwork groups may be performed by iteration through the appropriateprocessing steps described below and with any additional stepsappropriate for a given implementation.

In response to determining that a request to configure a social networkconversation dynamic inclusion threshold has been detected, the process400 identifies members of the social network group for which the requestto configure a social network conversation dynamic inclusion thresholdhas been detected at block 404. At block 406, the process 400 monitorssocial network conversations of the identified social network groupmembers. It should be noted that the monitoring of conversations of theidentified social network group members may be performed by analysis ofprevious social network conversations to expedite configuration of thesocial network conversation dynamic inclusion threshold, or may beperformed by monitoring future conversations over time subsequent to therequest to configure the social network conversation dynamic inclusionthreshold.

At block 408, the process 400 identifies response rates between members.The identification of the response rates between members may be furtherrefined based upon topic, time of day, or other factors as appropriatefor a given implementation to allow a determination of changes inresponse rates based upon opinions expressed during differentconversations and other factors usable to configure the social networkconversation dynamic inclusion threshold.

At decision point 410, the process 400 makes a determination as towhether one or more lack of responses has been identified. The lack ofresponse(s) may be identified across multiple conversations to determinewhether one or more social network group members normally respond tosocial network conversations, but do not respond under certainidentifiable situations/conditions. The respective identifiablesituations/conditions that result in the group members not respondingmay also be identified, including relationships between individual groupmembers and other situations/conditions.

In response to determining at decision point 410 that one or more lackof responses has not been identified, the process 400 returns to block406 and continues monitoring the social network conversations of thesocial network group. Alternatively, in response to determining atdecision point 410 that one or more lack of responses has beenidentified, the process 400 performs text analysis of posts to thesocial network conversation(s) with the detected lack of response(s) atblock 412. As described above, content of social network conversationsthat prematurely terminate may be suggestive of commentary that causesother group members not to comment or not to continue in a socialnetwork conversation. As such, the process 400 may identify these typesof text commentary that result in social network conversationsterminating without the intended amount of objective, diverse, andbalanced commentary.

At block 414, the process 400 determines a style of response and groupmember(s) that cause the lack of response(s) by the other groupmember(s). At block 416, the process 400 configures a social networkconversation dynamic inclusion threshold for one or more future socialnetwork conversation(s). The configured social network conversationdynamic inclusion threshold may be based upon a topic or subject ofconversation(s), time, number of responses/non-responses,responses/non-responses by particular members, and other factorsconsistent with the present description.

At block 418, the process 400 configures interception and evaluation ofposts of future social network conversation(s) among the social networkgroup using the configured social network conversation dynamic inclusionthreshold. For purposes of the present description, posts to beintercepted and evaluated may include any form of messages includingsocial network posts, emails, text messages, instant messages (IM),short message service (SMS) messages, blog posts, website postsassociated with online social communities, news feeds, and other formsof messages as appropriate for a given implementation. The process 400returns to decision point 402 and iterates as described above.

As such, the process 400 analyzes social network conversations,identifies situations in which certain group members do not respondwhere they would otherwise historically respond, and identifies thesesituations as a lack of response to be evaluated. The process 400further performs text analysis of the identified lack of response,determines a style of response that caused the lack of response, andconfigures and deploys a social network conversation dynamic inclusionthreshold.

FIG. 5 is a flow chart of an example of an implementation of a process500 for performing and dynamically adjusting dynamic inclusionthresholds for social network conversations. The process 500 representsa computer-implemented method of performing the dynamic threshold-basedinclusion for social network conversations described herein. The process500 is depicted and described as a per-conversation process, thoughadditional processing to perform processing of multiple contemporaneousconversations (e.g., by multi-threaded operation) may be utilized asappropriate for a given implementation. Additionally, as describedabove, for purposes of the present description, posts to be interceptedand evaluated include any form of messages including social networkposts, emails, text messages, and other forms of messages as appropriatefor a given implementation. The post may additionally be considered afirst post in a thread or any intermediate post for which a conversationhas been configured with one or more social network conversation dynamicinclusion thresholds.

At decision point 502, the process 500 make a determination as towhether a post associated with a social network conversation has beenintercepted. In response to determining that a post has beenintercepted, the process 500 makes a determination at decision point 504as to whether a social network conversation dynamic inclusion thresholdhas been configured for the post, such as being configured inassociation with the social network group member that generated the postor with the social network group associated with the social networkgroup member. In response to determining that a social networkconversation dynamic inclusion threshold has not been configured for thepost, the process 500 distributes the post to the social network groupwith which the post is associated at block 506, and the process 500returns to decision point 502 and iterates as described above.

Alternatively, in response to determining at decision point 504 that asocial network conversation dynamic inclusion threshold has beenconfigured for the post, the process 500 obtains the configured socialnetwork conversation dynamic inclusion threshold at block 508. At block510, the process 500 creates a distribution list for the post inaccordance with the respective social network group. Creation of thedistribution list for the post in accordance with the respective socialnetwork group may be performed using options described above forclustering and grouping, or otherwise as appropriate for the givenimplementation. At block 512, the process 500 identifies an initialdistribution subset of social network group members to which the postmay initially be distributed from the distribution list. The initialselected distribution subset of social network group members may bederived based upon group members from which historical responses aredetermined to be lacking (e.g., due potentially to dominant responsesfrom other members of the group, based upon being users involvedprimarily with different aspects of a subject matter area within thegroup, etc.). Group members that are not in the initial selecteddistribution subset may be included in the social network conversationat a later time. As such, the initial selected distribution subset maybe selected in accordance with differences in subject matter experienceamong the social network group members in the initial selecteddistribution subset of social network group members. Additionally, theinitial selected distribution subset may be selected in accordance withsimilarities in subject matter interest, such as selection of theinitial distribution subset according to group members with a first userinterest profile that matches a first subject, with inclusion at a latertime of users with a second user interest profile that matches a secondsubject.

At block 514, the process 500 distributes the post to the initialdistribution subset of group members on the distribution list. At block516, the process 500 monitors and analyzes text of additionalintercepted posts of the social network conversation and distributes theadditional intercepted posts to the initial distribution subset of groupmembers.

At decision point 518, the process 500 makes a determination, based uponthe text analysis of the intercepted posts and/or other criteria (e.g.,timeouts), as to whether a configured social network conversationdynamic inclusion threshold has been satisfied for the social networkconversation. As described above, the configured social networkconversation dynamic inclusion threshold may include an amount of timepassing since the intercepted post (e.g., a timeout, such as one minute,one hour, one day, etc.), quality and diversity of responses, sentimentof responses, attainment of a meta-threshold (e.g., there have been tennew posts, specific people have joined the conversation, etc.), a numberof responses or rate of responses increasing or decreasing, a sentimentthreshold (more positive responses than negative responses, etc.),subject matter drift, negativity tolerance criteria, age of posts,thread size, or other threshold, as appropriate for a givenimplementation.

In response to determining that the configured social networkconversation dynamic inclusion threshold has not been satisfied atdecision point 518, the process 500 makes a determination at decisionpoint 520 as to whether to adjust the configured social networkconversation dynamic inclusion threshold. Adjustment of the configuredsocial network conversation dynamic inclusion threshold may be performedover time, for example, responsive to determining that the socialnetwork conversation dynamic inclusion threshold has not been satisfiedin a reasonably timely manner, such as where the social networkconversation has become idle prior to any configured timeout within thesocial network conversation dynamic inclusion threshold or where someother factor is suggestive that the social network conversation dynamicinclusion threshold has been over constrained. As such, adjusting thesocial network conversation dynamic inclusion threshold operates as asocial network post distribution feedback mechanism to adjustdistribution of social network posts and may assist with ensuring thatintercepted posts get distributed to all group members in a timelymanner in circumstances where a particular conversation becomes idle andthe social network conversation dynamic inclusion threshold may not bereached or for other reasons as appropriate for a given implementation.

In response to determining not to adjust the configured social networkconversation dynamic inclusion threshold at decision point 520, theprocess 500 returns to block 516 and continues to monitor and analyzetext of additional posts of the social network conversation.Alternatively, in response to determining to adjust the configuredsocial network conversation dynamic inclusion threshold at decisionpoint 520, the process 500 adjusts the social network conversationdynamic inclusion threshold at block 522, and returns to block 516 andcontinues to monitor and analyze text of additional posts of the socialnetwork conversation.

Returning to the description of decision point 518, in response todetermining that the configured social network conversation dynamicinclusion threshold has been satisfied, the process 500 distributes theposts of the social network conversation to the remaining one or moresocial network group members on the distribution list at block 524. Theprocess 500 returns to decision point 502 and iterates as describedabove.

As such, the process 500 operates to intercept either initial orintermediate social network conversation posts, and to identify aninitial distribution subset of social network group members for initialinclusion in distribution of the post. The process 500 distributes thepost to the initial distribution subset of group members, and interceptsand monitors over time additional posts posted responsive to theintercepted post. The posts are analyzed for content and distributed tothe initial distribution subset of group members. The process 500evaluates one or more configured social network conversation dynamicinclusion thresholds, and adjusts the configured thresholds asappropriate for the particular thresholds and subsequent post content.In response to one or more of the configured social network conversationdynamic inclusion thresholds being satisfied, the remaining socialnetwork group members on the distribution list are included in thesocial network conversation and all posts associated with theconversation are distributed to the remaining social network groupmembers.

As described above in association with FIG. 1 through FIG. 5, theexample systems and processes provide dynamic inclusion thresholds forsocial network conversations. Many other variations and additionalactivities associated with dynamic inclusion thresholds for socialnetwork conversations are possible and all are considered within thescope of the present subject matter.

Those skilled in the art will recognize, upon consideration of the aboveteachings, that certain of the above examples are based upon use of aprogrammed processor, such as the CPU 202. However, the invention is notlimited to such example embodiments, since other embodiments could beimplemented using hardware component equivalents such as special purposehardware and/or dedicated processors. Similarly, general purposecomputers, microprocessor based computers, micro-controllers, opticalcomputers, analog computers, dedicated processors, application specificcircuits and/or dedicated hard wired logic may be used to constructalternative equivalent embodiments.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the art basedupon the teachings herein without departing from the scope and spirit ofthe invention. The subject matter was described to explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A computer-implemented method, comprising:distributing, in accordance with a social network conversation dynamicinclusion threshold that causes a first subset of social network groupmembers of a social network group to be included in a social networkconversation earlier than at least one other social network groupmember, social network posts of the social network conversation to thefirst subset of social network group members while delaying distributionof the social network posts of the social network conversation to the atleast one other social network group member; and distributing, inresponse to satisfaction of the social network conversation dynamicinclusion threshold, the social network posts of the social networkconversation to the at least one other social network group member. 2.The computer-implemented method of claim 1, further comprisingconfiguring the social network conversation dynamic inclusion thresholdresponsive to determining, by text analysis over time of commentary insocial network conversations by social network group members of thesocial network group, that at least one group member of the socialnetwork contributes to the social network conversations less often whena particular style of commentary is expressed by the at least one othersocial network group member.
 3. The computer-implemented method of claim1, further comprising: intercepting a social network post of the socialnetwork conversation; creating a distribution list for posts of thesocial network conversation in accordance with the social network group;identifying the first subset of social network group members as aninitial distribution subset of the social network group members; andwhere distributing, in accordance with the social network conversationdynamic inclusion threshold that causes the first subset of socialnetwork group members of the social network group to be included in thesocial network conversation earlier than the at least one other socialnetwork group member, the social network posts of the social networkconversation to the first subset of social network group members whiledelaying the distribution of the social network posts of the socialnetwork conversation to the at least one other social network groupmember comprises: contemporaneously distributing the intercepted socialnetwork post and additional intercepted social network posts of thesocial network conversation to the initial distribution subset of thesocial network group members on the distribution list, while delayingdistribution of the intercepted social network post and the additionalintercepted social network posts of the social network conversation toother social network group members of the social network group on thedistribution list.
 4. The computer-implemented method of claim 1,further comprising: intercepting, prior to delivery to social networkgroup members, the social network posts of the social networkconversation; analyzing text of the intercepted social network posts ofthe social network conversation; and determining, based upon the textanalysis of the intercepted social network posts, that the socialnetwork conversation dynamic inclusion threshold has been satisfied forthe social network conversation.
 5. The computer-implemented method ofclaim 1, further comprising adjusting, as social network postdistribution feedback, the social network conversation dynamic inclusionthreshold responsive to determining that the social network conversationdynamic inclusion threshold has been over constrained.
 6. Thecomputer-implemented method of claim 1, further comprising selecting thefirst subset of social network group members in accordance with one of:differences in subject matter experience among social network groupmembers in the first subset of social network group members; andsimilarities in subject matter interest.
 7. The computer-implementedmethod of claim 1, where the social network conversation dynamicinclusion threshold comprises at least one criterion selected from agroup consisting of: an elapsed amount of time, a quality of responses,a diversity of opinions expressed within responses, sentimentdistribution of responses, attainment of a specified quantity ofresponses, specific social network group members joining the socialnetwork conversation, a detected positive or negative change in a rateof responses, subject matter drift, age of posts, and thread size.
 8. Asystem, comprising: a memory; and a processor programmed to: distribute,in accordance with a social network conversation dynamic inclusionthreshold that causes a first subset of social network group members ofa social network group to be included in a social network conversationearlier than at least one other social network group member, socialnetwork posts of the social network conversation to the first subset ofsocial network group members while delaying distribution of the socialnetwork posts of the social network conversation to the at least oneother social network group member; and distribute, in response tosatisfaction of the social network conversation dynamic inclusionthreshold, the social network posts of the social network conversationto the at least one other social network group member.
 9. The system ofclaim 8, where the processor is further programmed to configure thesocial network conversation dynamic inclusion threshold responsive todetermining, by text analysis over time of commentary in social networkconversations by social network group members of the social networkgroup, that at least one group member of the social network contributesto the social network conversations less often when a particular styleof commentary is expressed by the at least one other social networkgroup member.
 10. The system of claim 8, where the processor is furtherprogrammed to: intercept a social network post of the social networkconversation; create a distribution list for posts of the social networkconversation in accordance with the social network group; identify thefirst subset of social network group members as an initial distributionsubset of the social network group members; and where in beingprogrammed to distribute, in accordance with the social networkconversation dynamic inclusion threshold that causes the first subset ofsocial network group members of the social network group to be includedin the social network conversation earlier than the at least one othersocial network group member, the social network posts of the socialnetwork conversation to the first subset of social network group memberswhile delaying the distribution of the social network posts of thesocial network conversation to the at least one other social networkgroup member, the processor is programmed to: contemporaneouslydistribute the intercepted social network post and additionalintercepted social network posts of the social network conversation tothe initial distribution subset of the social network group members onthe distribution list, while delaying distribution of the interceptedsocial network post and the additional intercepted social network postsof the social network conversation to other social network group membersof the social network group on the distribution list.
 11. The system ofclaim 8, where the processor is further programmed to: intercept, priorto delivery to social network group members, the social network posts ofthe social network conversation; analyze text of the intercepted socialnetwork posts of the social network conversation; and determine, basedupon the text analysis of the intercepted social network posts, that thesocial network conversation dynamic inclusion threshold has beensatisfied for the social network conversation.
 12. The system of claim8, where the processor is further programmed to adjust, as socialnetwork post distribution feedback, the social network conversationdynamic inclusion threshold responsive to determining that the socialnetwork conversation dynamic inclusion threshold has been overconstrained.
 13. The system of claim 8, where the processor is furtherprogrammed to select the first subset of social network group members inaccordance with one of: differences in subject matter experience amongsocial network group members in the first subset of social network groupmembers; similarities in subject matter interest; and where the socialnetwork conversation dynamic inclusion threshold comprises at least onecriterion selected from a group consisting of: an elapsed amount oftime, a quality of responses, a diversity of opinions expressed withinresponses, sentiment distribution of responses, attainment of aspecified quantity of responses, specific social network group membersjoining the social network conversation, a detected positive or negativechange in a rate of responses, subject matter drift, age of posts, andthread size.
 14. A computer program product, comprising: a computerreadable storage medium having computer readable program code embodiedtherewith, where the computer readable storage medium is not atransitory signal per se and where the computer readable program codewhen executed on a computer causes the computer to: distribute, inaccordance with a social network conversation dynamic inclusionthreshold that causes a first subset of social network group members ofa social network group to be included in a social network conversationearlier than at least one other social network group member, socialnetwork posts of the social network conversation to the first subset ofsocial network group members while delaying distribution of the socialnetwork posts of the social network conversation to the at least oneother social network group member; and distribute, in response tosatisfaction of the social network conversation dynamic inclusionthreshold, the social network posts of the social network conversationto the at least one other social network group member.
 15. The computerprogram product of claim 14, where the computer readable program codewhen executed on the computer further causes the computer to configurethe social network conversation dynamic inclusion threshold responsiveto determining, by text analysis over time of commentary in socialnetwork conversations by social network group members of the socialnetwork group, that at least one group member of the social networkcontributes to the social network conversations less often when aparticular style of commentary is expressed by the at least one othersocial network group member.
 16. The computer program product of claim14, where the computer readable program code when executed on thecomputer further causes the computer to: intercept a social network postof the social network conversation; create a distribution list for postsof the social network conversation in accordance with the social networkgroup; identify the first subset of social network group members as aninitial distribution subset of the social network group members; andwhere, in causing the computer to distribute, in accordance with thesocial network conversation dynamic inclusion threshold that causes thefirst subset of social network group members of the social network groupto be included in the social network conversation earlier than the atleast one other social network group member, the social network posts ofthe social network conversation to the first subset of social networkgroup members while delaying the distribution of the social networkposts of the social network conversation to the at least one othersocial network group member, the computer readable program code whenexecuted on the computer causes the computer to: contemporaneouslydistribute the intercepted social network post and additionalintercepted social network posts of the social network conversation tothe initial distribution subset of the social network group members onthe distribution list, while delaying distribution of the interceptedsocial network post and the additional intercepted social network postsof the social network conversation to other social network group membersof the social network group on the distribution list.
 17. The computerprogram product of claim 14, where the computer readable program codewhen executed on the computer further causes the computer to: intercept,prior to delivery to social network group members, the social networkposts of the social network conversation; analyze text of theintercepted social network posts of the social network conversation; anddetermine, based upon the text analysis of the intercepted socialnetwork posts, that the social network conversation dynamic inclusionthreshold has been satisfied for the social network conversation. 18.The computer program product of claim 14, where the computer readableprogram code when executed on the computer further causes the computerto adjust, as social network post distribution feedback, the socialnetwork conversation dynamic inclusion threshold responsive todetermining that the social network conversation dynamic inclusionthreshold has been over constrained.
 19. The computer program product ofclaim 14, where the computer readable program code when executed on thecomputer further causes the computer to select the first subset ofsocial network group members in accordance with one of: differences insubject matter experience among social network group members in thefirst subset of social network group members; and similarities insubject matter interest.
 20. The computer program product of claim 14,where the social network conversation dynamic inclusion thresholdcomprises at least one criterion selected from a group consisting of: anelapsed amount of time, a quality of responses, a diversity of opinionsexpressed within responses, sentiment distribution of responses,attainment of a specified quantity of responses, specific social networkgroup members joining the social network conversation, a detectedpositive or negative change in a rate of responses, subject matterdrift, age of posts, and thread size.